KR101821303B1 - System and Method for estimating object motion using the particle tracking model of differential wind coefficient mode - Google Patents

Abstract

The present invention relates to a marine search structure system and a method thereof. The marine search structure system uses a particle tracking model of a wind coefficient differential application method for predicting the object movement in an offshore environment. The marine search structure system includes: an accident information input unit and a weather information input unit for receiving accident information and weather information required for the movement of an object in an offshore environment; a search area setting unit for setting the search area with reference to the accident information and weather information received in advance; a grid flow rate information calculation unit which calculates the grid flow rate information calculation unit in the set search area; a grid wind information calculating unit which calculates the grid flow rate information calculation unit in the set search area; a wind coefficient estimator for calculating the optimal wind coefficient for wind strength; a particle tracking model executing unit which applies the grid flow rate information, grid wind information, and calculated wind coefficient to execute a particle tracking model; and a target object movement prediction unit which predicts the movement of the tracking target object with reference to the execution result of the particle tracking model executing unit.

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an object motion estimation system and a method for estimating an object motion using a particle tracking model,

More particularly, the present invention relates to a method and apparatus for predicting an object motion using a particle tracking model in which a wind coefficient is differentially applied, To a motion estimation system and method.

The International Maritime Organization (IMO) is an international organization governing the establishment and amendment of substantive international standards for maritime safety, security and marine pollution prevention. IMO decisions have a significant impact on the marine industry.

In order to provide effective support for the prevention and prevention of ship accidents, the IMO has established the International Maritime Safety Convention (SOLAS) and the SAR Report (SAR) for the rapid search and rescue of ships' Ship Reporting System (SRS).

In some countries, such vessel reporting systems are forcibly or arbitrarily enforced. For the purpose of safety and management of fisheries resources, the Vessel Monitoring System, which introduces satellite communication technology to the concept of SRS, is operated.

In the case of Korea, the Maritime Safety Act revised on March 24, 2006 provided legal basis for implementation of VMS. On November 1, 2007, the "Regulations on the installation standards of the ship's location transmitter" were announced, and detailed standards for the type, installation and operation of the VMS system were established.

According to these notices, VMS devices are installed and operated on ships of a certain size or more.

In addition, the introduction of the Global Maritime Distress and Safety System (GMDSS) allows the maritime distress communication method to be used as a distress communication method by DSC (Digital Selective Calling) It is changing.

In Korea, various radio stations such as the rescue station for rescue wireless communication, the fisheries information communication station and the port communication coast station are operated independently for their respective tasks.

However, most coast stations still operate by way of receiving distress signals by existing voice telephones, and are not coordinated with each other.

In the case of GMDSS, it is possible to construct a structure in a short time because the location information can be immediately announced by the satellite EPIRB (Emergency Position Indication Radio Beacons) in case of a large-sized ship disaster. However, a small ship (non- GMDSS line) , There is no obligation to install the EPIRB or the like, and when there is no automatic notification means at the time of the distress, the fact that the distress is notified using the fishery radio or the cellular phone at the time of the distress accident.

Such small-sized marine casualty accidents are caused by accidents directly linked to human life safety. However, since the automatic structure transmission system such as EPIRB is not equipped, rapid structure can not be expected due to the difficulty of grasping the distress situation and difficulty in finding the distress location. It is true.

In addition, since it is impossible to confirm the fall of not only a small-sized ship but also a boarding person aboard a ship, it is difficult to search for aboarded persons who are missing at the time of a vessel accident.

In other words, in the event of a maritime distress, rapid location of the victim is the most important factor in search and rescue operations.

Prior art search and rescue activities are carried out in anticipation of rescue sites based on the location identified at the time of the rescue request or the distress report of the witness.

However, there is a technical difficulty in accurately estimating the location of the victim when a long time has passed to move to the distress point.

In order to solve such a problem, in the prior art, particle tracking models for predicting the movement of an object in the sea have been developed and used in a system for marine search and rescue, but the accuracy is not high and there is a problem in terms of reliability.

Particularly, there is a problem that accuracy of object tracking and motion prediction is deteriorated by applying a single wind coefficient for each object when constructing and executing a particle tracking model for predicting the movement of an object in the sea.

Korean Patent Publication No. 10-2015-0129898 Korean Patent No. 10-1534620

The present invention solves the problem of a system and method for predicting the movement of an object in the sea such as the prior art. In the particle tracking model, the wind coefficient is differently applied according to the intensity of the wind, And a method of predicting an object motion using a particle tracking model in which a wind coefficient is increased.

The present invention calculates the distance difference between the position of the visual drift part such as the result of the particle tracking at every hour and predicts the accuracy of the drift prediction within a radius of 1 km within a radius of 1 km, The object of the present invention is to provide a system and method for predicting an object motion using a differential particle tracking model.

The present invention relates to a method and apparatus for estimating a particle tracking model by performing drift prediction every twelve hours in a drift section traveling path every twelve hours, comparing the buoy movement with a predicted value of the model, A motion prediction system and method are provided.

The present invention reproduces the surface layer flow using a buoy having a diameter of 25 cm, a height of 20 cm, and a buoyancy of 50 N, thereby obtaining an optimum wind coefficient value with respect to wind intensity (m / s) (Wind strength) + 0.0636, in which the wind coefficient is differently applied.

The objects of the present invention are not limited to the above-mentioned objects, and other objects not mentioned can be clearly understood by those skilled in the art from the following description.

In order to accomplish the above object, an object motion prediction system using a particle tracking model in which a wind coefficient is differentially applied according to the present invention includes an accident information input unit for receiving incident information and weather information required for predicting motion of an object at sea, A wind speed information calculation unit for calculating a wind velocity information for each lattice of the set search area and a lattice wind information calculation unit for calculating lattice wind information of the set search area, A wind speed estimator for calculating an optimum wind count value for the wind intensity, a particle classifier for executing a particle tracking model by applying the wind speed information per lattice, wind information per lattice, Tracking model execution part: The movement of the object to be tracked is determined based on the execution result in the particle tracking model execution part And an object predicting unit for estimating an object motion.

Here, the particle tracking model construction unit for calculating the distance difference between the position of the visual drifting portion and the particle drifting model by constructing the particle tracking model by evaluating the accuracy of the drift prediction with the ratio of the drifting buoy within the reference radius, And further comprising:

The wind coefficient calculation unit is characterized by calculating an optimum wind coefficient value with respect to wind intensity as: wind coefficient = -0.0041 x (wind strength) + 0.0636.

According to another aspect of the present invention, there is provided a method for predicting an object motion using a particle tracking model in which a wind coefficient is applied differentially according to the present invention. The object tracking method includes: inputting information necessary for predicting motion of an object in a sea; Setting a search area in the search area setting unit based on the accident information and the weather information, calculating flow information for each lattice and lattice wind information of the search area set by the lattice flow information calculating unit and lattice wind information calculating unit Calculating the optimum wind coefficient value for the wind intensity in the wind coefficient estimating section, executing the particle tracking model by applying the flow velocity information per grid, the wind information per grid, and the calculated wind coefficient in the particle tracking model execution section And a motion estimation unit for estimating the motion of the object to be tracked based on the particle tracking model execution result ; It comprises the features.

Here, in the step of calculating the wind coefficient value, the optimum wind coefficient value with respect to wind intensity is calculated as wind coefficient = -0.0041 x (wind strength) + 0.0636.

The object motion prediction system and method using the particle tracking model in which the wind coefficient is differently applied according to the present invention has the following effects.

First, the accuracy of object tracking is improved by differentiating wind factors according to the wind intensity in the particle tracking model for predicting the movement of objects in the sea.

Secondly, by calculating the distance difference of the position of the visual drift part such as the result of the particle tracking every hour, the accuracy of the drift prediction is evaluated and verified at the ratio of the drift buoy within the reference radius of the prediction result, Can be constructed.

Third, it is applied effectively to the system for marine search and rescue by increasing the accuracy of object tracking and motion prediction by differentiating wind factors according to the wind intensity when constructing and executing the particle tracking model for predicting the movement of objects in the sea. can do.

FIG. 1 is a block diagram of an object motion prediction system using a particle tracking model to which a wind coefficient is differentially applied according to the present invention.
Fig. 2 is a diagram showing a moving path of a moving part used for the verification of the particle tracking model
Fig. 3 is a diagram showing a comparison between the predicted values of the buoy movement and the particle tracking model by performing drift prediction
4 is a graph showing an optimal wind coefficient distribution for wind strength
FIG. 5 is a graph showing a time-based accuracy according to the wind coefficient difference application according to the present invention
FIG. 6 is a flow chart illustrating a method of predicting an object motion using a particle tracking model to which a wind coefficient is differentially applied according to the present invention.

Hereinafter, a preferred embodiment of the object motion prediction system and method using the particle tracking model to which the wind coefficient is applied according to the present invention will be described in detail as follows.

The features and advantages of an object motion prediction system and method using a particle tracking model to which a wind coefficient according to the present invention is applied differentially will be apparent from the following detailed description of each embodiment.

1 is a block diagram of an object motion prediction system using a particle tracking model to which a wind coefficient according to the present invention is applied differently.

FIG. 2 is a block diagram showing a moving path of a moving particle used in the verification of the particle tracking model, and FIG. 3 is a diagram showing a comparison of the prediction values of the particle moving model and the particle moving model by performing drift prediction.

In order to increase the accuracy of the particle tracking model, a particle tracking model is constructed in which the object tracking accuracy is enhanced by applying different wind factors according to the wind intensity. In order to increase the accuracy of the particle tracking model, And estimating the accuracy of the drift prediction with the ratio of the drift buoy located within a radius of 1 km.

Especially, the drift prediction is carried out every 12 hours for every 12 hours in the drift section, and the particle tracking model is verified by comparing the buoy movement with the predicted value of the model. The optimum wind direction (wind speed, m / s) The coefficient value is calculated as the wind coefficient = -0.0041 x (wind strength) + 0.0636.

The object motion prediction system using the particle tracking model in which the wind coefficient according to the present invention is applied is a particle tracking model constructed through a verification step and connected to a weather center, a control center, and a marine structure center through a wired, wireless or wired / Is applied.

As shown in FIG. 1, an object motion prediction system using a particle tracking model in which a wind coefficient is differentially applied according to the present invention includes an accident information input unit 10 for receiving accident information to obtain information necessary for predicting motion of an object at sea, A weather information input unit 11 for inputting weather information, a search area setting unit 12 for setting a search area on the basis of input accident information and weather information, a grid for calculating flow velocity information for each grid in the set search area, A lattice-by-lattice wind information calculating unit 14 for calculating lattice-specific wind information of the set search area and a lattice-based wind information calculating unit 14 for calculating an optimum wind coefficient value for the wind intensity (wind velocity, m / s) , Wind coefficient = -0.0041 × (wind strength) + 0.0636, and a particle counting module (15) for executing particle tracking model by applying lattice velocity information, lattice wind information, and estimated wind coefficient It includes an enemy model execution unit 16, and, the object motion predicting unit 17 for predicting the motion of the tracking target object based on the execution results of the particle tracking model execution unit 16.

Here, the accident information includes the accident occurrence position information of the sea, and the weather information includes the wind direction, the wind speed, the wave and the bird information provided by the weather center and the like, and is not limited to these information.

In order to increase the accuracy of the particle tracking model, the object motion prediction system using the particle tracking model in which the wind coefficient according to the present invention is applied differently calculates the distance difference of the position of the visual drift portion such as the particle tracking prediction result every hour And a particle tracking model building unit for estimating the accuracy of the drift prediction with a ratio of the drift buoy located within a radius of 1 km to construct a particle tracking model.

The particle tracking model is for predicting the motion of an object in the sea, and the essential elements and calculation of the particle tracking model are as follows.

Basically, two main input data (velocity field, wind field) are required for particle tracking prediction. The velocity field means velocity information for each lattice point, and wind field means wind information for each lattice point. And generally uses numerical model results.

An additional basic element is the wind coefficient, which is applied differently depending on the characteristics (volume, density, shape, etc.) of the object.

Accurate particle tracking requires precise flow rates, winds, and appropriate wind factor settings.

FIG. 2 shows the results of field observations performed to verify the particle tracking model applied to the present invention. The results are shown in FIG. .

And FIG. 3 shows the result of verification of the particle tracking model applied to the present invention.

The drift prediction is carried out for 24 hours every 12 hours in the drift section, and the wind speed is 0.032.

The accuracy of the drift prediction is calculated by calculating the distance difference of the position of the visual drift buoy at the same time as the time of each particle tracking prediction and estimating the ratio of the drift buoy to the position within the reference radius of 1 km.

It is a matter of course that the reference radius of 1 km can be determined differently by determining the distant viewable distance of the floating body at 1 km from the sea.

In Fig. 3, the red line is the drifting portion movement route, and the blue line is the drift prediction result.

FIG. 4 is a graph showing an optimal wind coefficient distribution for the wind strength, and FIG. 5 is a graph showing time-based accuracy according to the wind coefficient difference application according to the present invention.

FIG. 6 is a flowchart illustrating an object motion prediction method using a particle tracking model to which a wind coefficient according to the present invention is applied differentially.

In order to find the optimum wind coefficient used in the particle tracking model building unit according to the present invention, the particle tracking is performed every 24 hours at an interval of 0.002 from 0.02 to 0.05,

The optimal wind coefficient value for wind intensity is calculated as wind coefficient = -0.0041 × (wind strength) + 0.0636.

It is a matter of course that such a wind coefficient estimation equation can be varied depending on the type of object.

As a result, the model coincidence among the wind coefficients is improved by more than 10% compared with the wind coefficient of 0.032 which is the highest.

As shown in FIG. 6, the object motion prediction method using the particle tracking model in which the wind coefficient is differently applied according to the present invention,

A particle tracking model is constructed by evaluating the accuracy of the drift prediction with a ratio that the drift buoy is located within a radius of 1 km of the prediction result, And the weather information input unit 11 to input information necessary for predicting the motion of an object at sea (S601)

Then, a search area is set on the basis of the accident information and the weather information inputted from the search area setting part 12, and the grid of the search area set by the flow velocity information calculation part 13 and lattice- And calculates wind information per lattice of the set search area (S602)

Then, an optimal wind coefficient value for the wind intensity (wind speed, m / s) is calculated by the wind coefficient calculation unit 15 as: wind coefficient = -0.0041 x (wind strength) + 0.0636 (S603)

The particle tracking model execution unit 16 executes the particle tracking model by applying the lattice velocity information, the lattice wind information, and the wind coefficient calculated in the particle tracking model execution unit 16, and based on the particle tracking model execution result in the object motion prediction unit 17 The motion of the object to be tracked is predicted (S604)

The object motion prediction system and method using the particle tracking model in which the wind coefficient is different according to the present invention can improve the object tracking and motion prediction accuracy by applying a wind coefficient differently according to the intensity of the wind during the particle tracking model, Search and rescue systems.

As described above, it will be understood that the present invention is implemented in a modified form without departing from the essential characteristics of the present invention.

It is therefore to be understood that the specified embodiments are to be considered in an illustrative rather than a restrictive sense and that the scope of the invention is indicated by the appended claims rather than by the foregoing description and that all such differences falling within the scope of equivalents thereof are intended to be embraced therein It should be interpreted.

10. Accident information input section 11. Weather information input section
12. Navigation area setting unit 13. Velocity information calculation unit for each lattice
14. Wind information calculation part by lattice 15. Wind coefficient calculation part
16. Particle tracking model execution unit 17. Object motion prediction unit

Claims (5)

A particle tracking model construction unit for calculating a distance difference between the position of the visual drifting portion such as the time-based particle tracking prediction result and evaluating the accuracy of the drift prediction at a ratio of the drifting buoy within the reference radius of the prediction result;
An accident information input unit and a weather information input unit for receiving accident information and weather information necessary for predicting motion of an object at sea;
A search area setting unit for setting a search area on the basis of input accident information and weather information;
A lattice wind velocity information calculation unit for calculating lattice velocity information of a set search area and a lattice wind information calculation unit for calculating lattice wind information of a set search area;
Wind coefficient estimating wind factor according to wind intensity;
A particle tracking model execution unit for executing a particle tracking model by applying flow velocity information per grid, wind information per grid, and estimated wind coefficient;
And an object motion prediction unit for predicting a motion of the object to be trained on the basis of the result of execution in the particle tracking model execution unit,
A particle motion estimation system using a particle tracking model in which a wind coefficient is differentiated, characterized in that an object tracking and a motion prediction are performed by applying a wind coefficient differently according to the intensity of wind when a particle tracking model is executed. delete The wind power generation system according to claim 1,
Wherein the wind speed coefficient is calculated as: wind coefficient = -0.0041 x (wind strength) + 0.0636. The particle tracking model construction part calculates the distance difference of the position of the visual drift buoy at the same time as the result of the particle tracking at every hour and constructs the particle tracking model by evaluating the accuracy of the drift prediction with the ratio of the drift buoys located within the reference radius ;
Receiving accident information and weather information necessary for predicting the motion of an object at sea in an accident information input unit and a weather information input unit;
Setting a search area in a search area setting unit based on accident information and weather information input through an accident information input unit and a weather information input unit;
Calculating flow velocity information and lattice wind information of each lattice of the search area set by the lattice-specific flow velocity information calculating unit and lattice-specific wind information calculating unit;
Calculating a wind coefficient value according to the wind intensity in the wind coefficient estimating section;
In the particle tracking model execution part, the particle tracking model is executed by applying the grid velocity information, the lattice wind information and the calculated wind coefficient, and based on the particle tracking model execution result, The method comprising:
A method of predicting an object motion using a particle tracking model in which a wind coefficient is differentiated, characterized in that object tracking and motion prediction are performed by differentiating wind factors according to the wind intensity at the time of executing the particle tracking model. 5. The method according to claim 4, wherein, in estimating the wind coefficient value,
A method for predicting an object motion using a particle tracking model to which a wind coefficient is applied differently is characterized in that a wind coefficient value according to wind intensity is calculated as wind coefficient = -0.0041 x (wind strength) + 0.0636.

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